Articles article
Artificial Intelligence‑Empowered Nursing Practice: Current Status, Challenges and Development Paths
Abstract
Under the macro background of medical digital transformation, artificial intelligence technology has gradually penetrated into the nursing industry, and has a far-reaching impact on the traditional nursing service mode and discipline development system. Based on the macro industry perspective, this paper conducts research from the three dimensions of application status, practical challenges and development path, comprehensively sorts out the overall application trend and industry value of intelligent technology in the nursing field, objectively analyzes the ethical risks, adaptation problems and industry weaknesses that are common in the process of technology implementation, and puts forward optimization ideas for the long-term development of the adaptive nursing industry in combination with the development trend of digital medicine. The research aims to provide a macro reference for the standardized and systematic development of intelligent nursing, and help the digital and stable transformation and high-quality development of nursing discipline.
Keywords
References
[1]Wang, B., Shi, X., Han, X., & Xiao, G. (2024). The digital transformation of nursing practice: an analysis of advanced IoT technologies and smart nursing systems. Frontiers in medicine, 11, 1471527. https://doi.org/10.3389/fmed.2024.1471527
[2]Martinez-Ortigosa, A., Martinez-Granados, A., Gil-Hernández, E., Rodriguez-Arrastia, M., Ropero-Padilla, C., & Roman, P. (2023). Applications of Artificial Intelligence in Nursing Care: A Systematic Review. Journal of nursing management, 2023, 3219127. https://doi.org/10.1155/2023/3219127
[3]Bai, Y., Gu, B., & Tang, C. (2025). Enhancing Real-Time Patient Monitoring in Intensive Care Units with Deep Learning and the Internet of Things. Big data, big20240113. Advance online publication. https://doi.org/10.1089/big.2024.0113
[4]Li, F., Wang, S., Gao, Z., Qing, M., Pan, S., Liu, Y., & Hu, C. (2025). Harnessing artificial intelligence in sepsis care: advances in early detection, personalized treatment, and real-time monitoring. Frontiers in medicine, 11, 1510792. https://doi.org/10.3389/fmed.2024.1510792
[5]Olivera, P., Danese, S., Jay, N., Natoli, G., & Peyrin-Biroulet, L. (2019). Big data in IBD: a look into the future. Nature reviews. Gastroenterology & hepatology, 16(5), 312–321. https://doi.org/10.1038/s41575-019-0102-5
[6]Yakusheva, O., Bouvier, M. J., & Hagopian, C. O. P. (2025). How Artificial Intelligence is altering the nursing workforce. Nursing outlook, 73(1), 102300. https://doi.org/10.1016/j.outlook.2024.102300
[7]Dailah, H. G., Koriri, M., Sabei, A., Kriry, T., & Zakri, M. (2024). Artificial Intelligence in Nursing: Technological Benefits to Nurse's Mental Health and Patient Care Quality. Healthcare (Basel, Switzerland), 12(24), 2555. https://doi.org/10.3390/healthcare12242555
[8]Bai, S., Zheng, J., Wu, W., Gao, D., & Gu, X. (2024). Research on healthcare data sharing in the context of digital platforms considering the risks of data breaches. Frontiers in public health, 12, 1438579. https://doi.org/10.3389/fpubh.2024.1438579
[9]Wang, X., Xie, Y., Chen, X., Yang, J., Li, R., Gao, W., Yan, Z., Zhou, H., & Ye, Z. (2026). Securing Federated Learning With Blockchain in the Medical Field: Systematic Literature Review. Journal of medical Internet research, 28, e79052. https://doi.org/10.2196/79052
[10]Felzmann, H., Fosch-Villaronga, E., Lutz, C., & Tamò-Larrieux, A. (2020). Towards Transparency by Design for Artificial Intelligence. Science and engineering ethics, 26(6), 3333–3361. https://doi.org/10.1007/s11948-020-00276-4
[11]Wei, H., & Watson, J. (2026). Preserving Professional Human Caring in Nursing in the Era of Artificial Intelligence. ANS. Advances in nursing science, 49(1), 70–76. https://doi.org/10.1097/ANS.0000000000000573
[12]Yıldız E. (2025). Artificial Intelligence in Mental Health Nursing: Balancing Clinical Efficiency and the Human Touch-A Quest for a New Synthesis. Journal of psychiatric and mental health nursing, 32(4), 946–952. https://doi.org/10.1111/jpm.13173
[13]Ibuki, T., Ibuki, A., & Nakazawa, E. (2024). Possibilities and ethical issues of entrusting nursing tasks to robots and artificial intelligence. Nursing ethics, 31(6), 1010–1020. https://doi.org/10.1177/09697330221149094
[14]Jobst, S., Lindwedel, U., Marx, H., Pazouki, R., Ziegler, S., König, P., Kugler, C., & Feuchtinger, J. (2022). Competencies and needs of nurse educators and clinical mentors for teaching in the digital age - a multi-institutional, cross-sectional study. BMC nursing, 21(1), 240. https://doi.org/10.1186/s12912-022-01018-6
[15]Li, P., Tan, R., Yang, T., & Meng, L. (2025). Current status and associated factors of digital literacy among academic nurse educators: a cross-sectional study. BMC medical education, 25(1), 16. https://doi.org/10.1186/s12909-024-06624-3
[16]Brown, J., Pope, N., Bosco, A. M., Mason, J., & Morgan, A. (2020). Issues affecting nurses' capability to use digital technology at work: An integrative review. Journal of clinical nursing, 29(15-16), 2801–2819. https://doi.org/10.1111/jocn.15321
[17]Terry, J., Davies, A., Williams, C., Tait, S., & Condon, L. (2019). Improving the digital literacy competence of nursing and midwifery students: A qualitative study of the experiences of NICE student champions. Nurse education in practice, 34, 192–198. https://doi.org/10.1016/j.nepr.2018.11.016
[18]Wangpitipanit, S., Lininger, J., & Anderson, N. (2024). Exploring the deep learning of artificial intelligence in nursing: a concept analysis with Walker and Avant's approach. BMC nursing, 23(1), 529. https://doi.org/10.1186/s12912-024-02170-x
[19]Zhang, J., & Zhang, Z. M. (2023). Ethics and governance of trustworthy medical artificial intelligence. BMC medical informatics and decision making, 23(1), 7. https://doi.org/10.1186/s12911-023-02103-9
[20]Al-Jaroodi, J., Mohamed, N., & Abukhousa, E. (2020). Health 4.0: On the Way to Realizing the Healthcare of the Future. IEEE access : practical innovations, open solutions, 8, 211189–211210. https://doi.org/10.1109/ACCESS.2020.3038858
[21]Zhang, Z., Hou, J., Xu, C., Li, H., & Wan, H. (2026). Nurses' experiences regarding role boundaries in collaborative AI-Assisted nursing: A meta-synthesis. Social science & medicine (1982), 403, 119385. https://doi.org/10.1016/j.socscimed.2026.119385